Quantdinger
AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading
by brokermr810 · brokermr810/QuantDinger
Install
See GitHub repository for installation instructions.
How to use Quantdinger with Claude
Quantdinger is a Model Context Protocol (MCP) server that gives Claude and other AI agents direct access to search capabilities. Once installed, you can use it in Claude Desktop, Cursor, VS Code with GitHub Copilot, or any MCP-compatible client.
Setup
- Clone or install from the GitHub repository
- Follow the README for environment setup and credentials
- Add the server to your MCP client config (claude_desktop_config.json or .cursor/mcp.json)
- Restart your client — Quantdinger will appear in the available tools list
About Quantdinger
Quantdinger is an open-source MCP server in the Search category, built in Python. It connects Claude and other MCP-compatible clients to search systems directly. Source available on GitHub.
Use cases for Search MCP servers
- →Run semantic and keyword searches across multiple indices
- →Summarize and cluster search results automatically
- →Integrate external search APIs into AI agent workflows
- →Build RAG pipelines connecting AI to live search indexes
Where Quantdinger fits in an MCP workflow
Teams use Quantdinger to give Claude a direct bridge into search workflows, so routine actions happen inside the AI client instead of across separate tabs and dashboards.
Quantdinger can be connected to MCP clients by following the repository setup instructions, making it useful for teams that want AI access to search systems.
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